Investigations of basic radial
wood density (WD) in tropical trees revealed linear patterns and some
curvilinear patterns. Studies usually disregard longitudinal variations, which
are often considered to be similar to radial variations. This study aimed to
show (1) a new radial curvilinear WD pattern, (2) differences in amplitude
between radial and longitudinal gradients and (3) to partition WD variations
according to different scales in Parkia velutina, an emergent tree found
in Neotropical rain forests. We collected full discs from six felled trees and
radial cores from 10 standing trees to check WD variability, plus one dominant
axis per tree for analysis of height growth rates. This species showed very
high growth rates indicative of heliophilic habits. WD varied from 0.194 to
0.642 g/cm3. Such amplitude is rarely observed within the same tree.
Radial variation in WD was curvilinear, with an amplitude generally less than
the longitudinal amplitude. Consequently, in mature trees, WD values in the
crown were higher than those in the outer trunk. WD variations can be highly
significant at different scales. The variance partitioning also revealed that
the whole WD range of Parkia velutina is more accurately estimated
intra-individually when both longitudinal and radial gradient are covered.

Wood density is now considered as a
major tree functional ecological trait because it includes the expression of
the genome, the ecological temperament and the history of tree functioning.
Among tropical trees, basic wood density (WD), defined as wood dry mass divided
by fresh volume (Kollmann and Côté, 1968), varies between 0.1 to more than 1.2
g/cm3 (Chave et al., 2009; Zanne et al., 2009). This
huge variation between species is related to different stages of ecological
succession. Heliophilic species have a much lower WD than sciaphilic species
(Wiemann and Williamson, 1988; Nock et al., 2009). Although, variation
in WD has been shown to be highest between species (Maniatis et al.,
2011), both within species and within tree variation (especially in tropical
emergent species) are substantial (Nock et al., 2009; Osazuwa-Peters et
al., 2014; Plourde et al., 2015; Wassenberg et al., 2015).
Indeed, our knowledge about within tree WD variations and its functional
significance has increased significantly in recent decades.

Diameter at breast height (DBH), followed
by WD are the best predictors of above-ground biomass (AGB) and of carbon
sequestration by trees (Ketterings et al., 2001; Chave et al.,
2009, 2014; Vieilledent et al., 2012; Zhang et al., 2012).
Consequently, a better knowledge of radial and longitudinal variations in WD
within the tree will enable to more accurate estimates of the carbon stored by
a given ecosystem. This is particularly applicable in the case of tropical
forests, which contain a high diversity of tree species (Whitmore, 1990) and represent
the main stock of carbon (Lewis et al., 2009).

Reaching the canopy is challenging for
an individual tree due to high stand density and strong competition for light.
To face this challenge, trees have evolved different biomass allocation
strategies that influence both the range and the way that WD varies radially (i.e.
from pith to bark). At the lower end of the shade tolerance continuum, pioneers
and more generally heliophilic species increase rapidly in height to reach the
light as fast as possible. This rapid increase in height is enabled by the
production of low WD (Woodcock and Shier, 2002). When the tree crown reaches
the canopy, its environment changes and growth in height decreases in favour of
the development of the crown, which, in turn, creates mechanical stresses due
to the tree’s increasing self-weight and/or wind forces (Woodcock and Shier,
2002). This change triggers the production of relatively higher WD in order to
maintain mechanical stature (Wiemann and Williamson, 1988, 1989; Rueda and
Williamson, 1992; Woodcock and Shier, 2002; Nock et al., 2009).
Inversely, at the other end of the shade tolerance continuum, shade tolerant or
sciaphilic species grow more slowly and initially produce denser, stiffer more
resistant wood, which is interpreted as an adaptation to resist pests and the
falling leaves/branches of taller neighbouring trees (Woodcock and Shier, 2002;
Muller-Landau, 2004).

WD can thus vary radially within tree
(Wiemann and Williamson, 1988, 1989; Woodcock and Shier, 2002; Nock et al.,
2009; Hietz et al., 2013). This radial variation, estimated as the slope
of the regression of WD on the distance from the pith, is strongly correlated
with tree age but not with tree size, suggesting an ontogenetic control of
radial WD variation (Rueda and Williamson, 1992; De Castro et al., 1993;
Nock et al., 2009; Williamson and Wiemann, 2010, 2011; Williamson et
al., 2012). This assumption holds only for species with a linear pattern.
However further studies illustrated substantial diversity in radial gradients:
four main patterns of variation in radial WD are reported in the literature.
Patterns showing a linear radial increase with low values near the pith and
high density values near the bark (Panshin and De Zeeuw, 1980; Wiemann and
Williamson, 1988; De Castro et al., 1993; Williamson and Wiemann, 2010;
Osazuwa-Peters et al., 2014) are associated with early successional
behaviour (Woodcock and Shier, 2002), whereas patterns showing a linear radial
decrease with high values near the pith and lower density near the bark
(Panshin and De Zeeuw, 1980) are associated with late successional behaviour
(Woodcock and Shier, 2002). The two other WD radial patterns are nonlinear with
a concave or convex pattern (Williamson et al., 2012; Osazuwa-Peters et
al., 2014). However, any successional behaviour was seen to be associated
with the last non-monotonic pattern. Still, one could think that this pattern
characterizes a heliophilic strategy, as shown by Williamson et al.(2012) in Schizolobium parahyba a typical short-lived
Neotropical pioneer species.

Most studies focused on radial
variation in WD (Butterfield et al., 1993; Woodcock and Shier, 2002;
Nock et al., 2009; Williamson and Wiemann, 2010, 2011; Williamson et
al., 2012; Hietz et al., 2013; Schüller et al., 2013;
Osazuwa-Peters et al., 2014), whereas little is known about longitudinal
variation in WD (Rueda and Williamson, 1992; Wiemann and Williamson, 2014;
Wassenberg et al., 2015), probably because longitudinal pattern of wood
properties has generally been considered to be similar to radial pattern
(Lachenbruch et al., 2011) due to the same physiological age of the
cambium at tree base and at tree tip.

In this paper, we show the entire WD
pattern of a long-lived heliophilic forest tree by answering the two following
questions: (1) What do the radial and longitudinal variations in the WD of the
trees look like? (2) What is the pattern of radial variation in WD?

We chose Parkia velutina Benoist
(Leguminosae: Mimosoideae), an emergent forest tree widely but discontinuously
distributed in the Brazilian and Peruvian Amazon, French Guiana, eastern
Venezuela and in Colombia west of the Andes (Hopkins, 1986). Not used in French
Guiana, big trees are peeling for veneer industry in Brazil, when the heart is
healthy. This species usually has low values of WD (about 0.4 g/cm3,
Zanne et al., 2009), but is a long-lived heliophilic species, i.e. intermediate
between pioneer and hemi-tolerant, making this emergent Neotropical forest
species particularly attractive to investigate WD variations within a tree,
with respect to tree architecture and ontogeny.

Matériel et méthodes

Study site and climatic typology

The study was conducted at the Paracou
experimental site in the lowland tropical rainforest of French Guiana (5° 18’
N, 52° 55’ W) (Gourlet-Fleury et al., 2004). The site receives nearly
two-thirds of the annual 3,041 mm of precipitation between mid-March and
mid-June, and less than 50 mm per month in September and October. A daily mean
temperature of 25.8 °C is almost constant over the year. The experimental site
is a stand of old growth forest dominated by Leguminoseae, Chrysobalanaceae,
Lecythidaceae, Sapotaceae and Burseraceae (Sabatier and Prévost, 1989).

Tree sampling and measurements

Since we knew very little about P.
velutina, we first measured the height, diameter, architectural stages of
development, crown position in a population of 90 individual forest trees.
Height was assessed using a laser meter (Haglöf Vertex Laser L400) and diameter
was measured using a dendrometer placed higher than breast height (2-3 m) to
avoid buttress effects. In addition, we assessed crown architecture suspected
to significantly affect WD. Like many species, P. velutina reaches
its mature stage through a reiterative process (Oldeman, 1974), which changes
the tree’s architecture through the duplication of the architectural unit.
Three architectural stages of development (ASDs) were recorded (figure 1d):
ASD1 trees with sequential branches borne by an orthotropic trunk, ASD2 trees
with erect branches (“reiterated branches”) forming the future fork at the top
of the trunk and some sequential branches always present below the fork, and
ASD3 trees with reiterated branches forming a hemispherical shaped crown,
whereas sequential branches are no longer present. Among our 90 trees, we
classified 42 ASD1, 19 ASD2 and 29 ASD3 trees.

Figure 1.

a) Height as a function
of diameter (D) and of the architectural stage of development (ASD) of 90
trees of Parkia velutina. Closed symbols represent the sampled trees.
The red line represents the fitted function H=a*log(D)+b. b) Diameter (D) and
height according to the architectural stage of development (ASD).
Kruskal-Wallis tests are significant at α = 0.05. The different letters
correspond to significant differences between groups after post-hoc
multiple comparison. c) Length of last annual growth units (GUs) as a
function of tree diameter (D). d) Architectural stage of development (ASD) of
P. velutina.

Next, among the 90 trees, we selected
10: one ASD2 tree (N°4) and nine ASD3 trees (N°6, 7, 9, 10, 11, 12, 13, 14 and
N°15) (table I). From each, we extracted one radial wood core above breast
height (between 2 and 6 m from the base of the trunk) with a 5-mm diameter
increment borer, while a climber collected one dominant branch in the crown.

In addition, to be sure of observing
the entire range of WD variability, we felled three young trees (ASD1: N°1 and
N°2; ASD2: N°3) and two large adult trees (ASD3; N°5 and N°8, table I) among
the 90 forest trees plus a third adult tree (ASD3; N°16 growing in
the open condition in a large logging gap created 23 years ago). It was
not the biggest tree to avoid a hollow trunk (40 cm < D < 50 cm,
figure 1). For each of these six trees, three wood discs were collected between
the base of the trunk and the top of the crown: above breast height (between 2
and 6 m from the base of the trunk), below the fork and in the crown. In the
field, the discs and the radial wood cores were sealed in plastic bags and
plastic tubes, respectively, to prevent drying, and then stored in the
refrigerator until the measurements were made.

Measurements of basic wood density
(WD)

A diametral sample (i.e. bark to
bark through the pith) of 2*2 cm section was extracted from each wood disc
taken from the six felled trees (N°1, 2, 3, 5, 8 and 16) and tangentially cut
into 0.5 cm segments from bark to bark for the young trees (N°1, 2 and 3) and
into 1.5 cm segments for the adult’s trees (N°5, 8, 16), in such way that
ensured the pith was included in a single segment.

A 2 cm long outer segment (close to the
bark) was taken from the core of each 10 additional trees (N° 4, 6, 7, 9, 10,
11, 12, 13, 14 and N°15). In addition, for these 10 trees, complete wood discs
(~ 4 cm in diameter) were also collected from the higher part of dominant
branches.

In all cases, the bark and the pith
were discarded. Within 24 h of sampling, the green volume of each segment was
determined using the water displacement method. The wood samples were
oven-dried at 103 °C for 72 h before weighing on a 0.2 mg precision
SARTORIUS balance. The WD of each sample was calculated as the ratio of dry
mass to green volume (g/cm3, Kollmann and Côté, 1968).

Measurement of longitudinal growth
rates

As the height growth rate is indicative
of the development stage of the tree (juvenile, adult mature and senescent), we
investigated the height growth rate of the branches of each tree sampled. The
limits of the growth units (GUs) making up the axes were located by recognizing
morpho-anatomical markers that result from the rhythmic activity of the primary
meristems, and which persist in the bark and pith for several years (Barthélémy
and Caraglio, 2007). According to a study by Nicolini et al. (2012) on P.
velutina, we retrospectively identified, for different axes per tree, the
last successive GUs and measured their lengths.

Statistical analysis

We compared the basal diameter and
height of the three different architectural stages (ASD1, ASD2 and ASD3) in 90
trees using a nonparametric Kruskal-Wallis test followed by Tukey’s honest
significant difference test if the Kruskal-Wallis test was significant. The
same procedure was used to compare mean WDs among three heights (basal, under
the fork and in the crown) within each felled tree (N°1, 2, 3, 5, 8). Tree N°16
was excluded from this analysis because of its hollow trunk.

Because we wanted to study tree
behaviour according to tree size, the trees were classified in three groups as
a function of basal diameter and the mean length of the last annual GUs. The
first group (1) was composed of four trees (ASD1 and ASD2: N°1, 2, 3 and 4)
whose basal diameter was < 20 cm, and whose mean length of the last annual
GUs was 68 cm. The second group (2) was composed of five trees (N°5, 6, 7, 8
and 9) whose basal diameter ranged between 40 and 55 cm, and whose mean length
of the last annual GUs was 25 cm. The last group (3) was composed of the five
largest trees (N°11, 12, 13, 14 and 15) whose basal diameter ranged between 65
and 85 cm, and whose mean length of the last annual Gus was 7 cm. Tree N°10 was
excluded since it clearly did not fit in any group. We compared the WD in the
crowns and trunks of the three groups with a nonparametric Kruskal-Wallis test
followed by Tukey’s honest significant difference test if the Kruskal-Wallis
test was significant.

We performed a variance component
analysis in order to assess the contribution of WD variation among measurement
radius, measurement heights and individuals. A random effects model with three
nested levels of random effects (individuals/height/radius) was used to
estimate the proportion of variation in WD associated with individuals, height
and radius. The residual variation included variation associated with segments
plus measurement error.

Radial patterns of WD variations at
different heights and in different individuals were modelled using multilevel
linear mixed effect models (Pinheiro and Bates, 2000). As WD varies radially,
we used distance from the pith as a fixed effect and selected three nested
random factor levels that enabled modelling of WD at different scales: between
and within individuals. These three nested random factors levels were (1)
individual, (2) height within an individual and (3) sampled radius within
height.

As a curvilinear pattern exists
(Williamson et al., 2012; Osazuwa-Peters et al., 2014), we first
specified a full multilevel mixed-effects quadratic model, for which all terms
have random effects at all nested levels considered (table II). Let WDijkd
be the WD value of the dth 0.5 cm interval from
the pith of the kth radius within the jth
height within ith individual, our full species-level model is
expressed as follow:

where x is the distance from the pith,
and εijkd is the
within group error.

We also specified a full multilevel
mixed-effects linear model:

WDijkd = (β0+β0i+β0ij+β0ijk) + (β1+β1i+β1ij+β1ijk)* xijkd + εijkd

The most parsimonious model was
selected using a series of reduced models that vary in their inclusion of
random effects (table II). We derived both quadratic and linear models and
computed the corrected Akaike information criterion (AICc) for each derived
model. We selected the model with the lowest AICc.

Description of the fitted linear
mixed-effects models. The table presents the inclusion of both fixed and random
effects for each model (X). For each model, the number of freedom degrees as
well as the corrected Akaike Information criterion (AICc) are presented. The
ΔAICc is equal to the difference between the AICc of the model and the lower
AICc.

Allometry, architecture and
longitudinal growth rates at the population scale

The diameter and height of the measured
trees ranged from 3 to 80 cm and from 3 to 38 m, respectively (figure 1a). The
height/diameter relationship for P. velutina trees of Paracou was fitted
by a linear model involving log(D) (figure 1a, red line). In small trees (D
< 25 cm), height increased sharply with increasing diameter but slowed down
in bigger trees (D > 25 cm). Height and diameter efficiently distinguished
the different development stages of our samples. Only ASD1 trees were observed
in the first part of the curve (D mean = 12.6 ± 4.3 cm and H mean = 14.2 ± 4.8
m), whereas ASD3 trees were found only in the second part of the curve (D mean
= 52.2 ± 16.1 cm and H mean = 31.6 ± 5.1 m). ASD2 trees symbolized the
transition between the two other stages (D mean = 21.5 ± 7.3 cm and H mean =
22.5 ± 6.5 m). Although the different architectural stages overlapped a little,
we observed significant differences in diameter (Kruskal-Wallis test; p-value
< 0.001) and in height (Kruskal-Wallis test; p-value < 0.001) in the ASD
classes (figure 1b). On the basis of the mean length of the last annual GU as a
function of tree diameter (figure 1c), we also distinguished three groups that
differed significantly both in trunk diameter (Kruskal-Wallis test; p-value
< 0.001) and in the length of the last annual GU (Kruskal-Wallis test; p-value
< 0.001). To sum up, trees with the biggest diameters had the shortest GU
and conversely. So, we were able to distinguish two vigour groups among the
ASD3 trees: young adult trees and pre-senescent adult trees.

Contribution of WD variation among
individuals, heights, and radius

Variance component analysis depicted
the contribution of the three nested factors (individual/height/radius) to the
overall variation of WD (figure 2). Surprisingly, the measurement height within
individuals contributes to the bulk of the variation in WD (67%). Variation
among segments within radius is the second contributor to WD variations with
32%. Finally, the variation attributed to the individual level and between
radius within height are marginal, with < 1% and < 0.1 % respectively.
Height and among-segments levels being the most important, this variance
partitioning analysis suggests strong longitudinal and radial variation in WD.

Figure 2.

Variance component
analysis depicting the contribution of the three nested factors (individual/height/radius)
to the overall variation of WD.

Longitudinal variations
in WD with ontogeny and within the sampled trees

The outer WD at the base of the trunk
increased gradually from group 1 to group 3 (figure 3), while the WD values in
the crown top increased significantly from group 1 to group 2 but not from
group 2 to group 3 (figure 3). Finally, the WD at the top of the crown was
significantly higher than outer WD at the base of the trunk in both groups 2
and 3 (ASD3 trees), but not in group 1 (ASD1 and ASD2, figure 3).

Figure 3.

Mean basic wood density
(WD, in g/cm3) at the base of the trunk and at the top of the
crown from the 2 cm outermost segments of the three ontogeny groups (Group 1:
n = 4, diameter < 20 cm, Group 2: n = 5, diameter between 40-55 cm, Group
3: n = 5, diameter between 65-85) of trees of Parkia velutina. For
each group, a Kruskal-Wallis test was used to compare the two heights; the
star indicates a significant difference (P > 0.05). For each height, a
Kruskal-Wallis test was used to compare the three groups; pairs with the same
letter are not significantly different (P > 0.05). Kruskal-Wallis
test was followed by post-hoc multiple comparison tests if the
Kruskal-Wallis test was significant.

In the six felled trees, WD ranged from
0.194 to 0.642 g/cm3 with an average of 0.392 g/cm3,
however the same range was also observed in a single tree (figure 4). Mean WD
in the crown was higher than mean WD at the base of the trunk and under the
fork. Above all, in three adult trees (N°5, 8 and 16), the WD under the fork
was between WD at the base of the trunk and WD in the crown. A visual
assessment was sufficient to state that the within disc variability in the
crown was less than that in the trunk.

Figure 4.

Radial and longitudinal
variation in basic wood density (WD, in g/cm3) according to
distance from the pith in six Parkia velutina trees (N°1, 2, 3, 5, 8
and 16). Mean basic wood density (WD) for the three heights (on the trunk
(between 2 and 6 m, in black), under the fork (in red) and in the crown (in
blue) for the six felled trees. Kruskal-Wallis tests were used to compare the
three groups within each individual; pairs with the same letter are not
significantly different (P > 0.05). Kruskal-Wallis tests were followed by post-hoc
multiple comparison tests if the Kruskal-Wallis test was significant.

Mixed-effects modelling of radial
variations in WD

The radial gradient in WD was best
fitted by the quadratic regression model (figure 4). AICc is the lowest for the
m4 model (AICc = -914.27, table II). This model includes random effect on
both linear and quadratic terms for all levels considered. Nevertheless, it
only includes random effect on intercept for height, suggesting that the WD at
stem centre varies with measurement height. In counterpart, the absence of
random effect on intercept for the individual level suggests that the mean WD
along the stem centre does not varies between trees.

Table II.

Description of the fitted linear
mixed-effects models. The table presents the inclusion of both fixed and random
effects for each model (X). For each model, the number of freedom degrees as
well as the corrected Akaike Information criterion (AICc) are presented. The
ΔAICc is equal to the difference between the AICc of the model and the lower
AICc.

According to the mixed-effect modelling
and the visual assessment of WD variations (figure 4), the lowest values of WD
were observed in the inner wood at the base of the trunk whereas highest values
were recorded in the crown.

In P. velutina N°16, which was
an isolated tree, all the outer parts of the basal trunk reached values similar
to those observed in the top of the crown (figure 4). This observation agrees
with the observed non-significant differences in WD between the base of the
trunk and under the fork in this individual.

Discussion

Parkia velutina, a heliophilic long lived trees

In our study, we combined a precise
description and fine-scale measurement of WD variability according to the tree
ontogenic development and architecture. These approaches allowed us to
highlight the fact that growth rate varies considerably with tree diameter and
height. These notable variations can be explained by the ecological temperament
of P. velutina, which is between that of a strictly heliophilic species
like Cecropia obtusa, for example, and a hemi-tolerant species like Dicorynia
guianensis.

Like a pioneer species, P. velutina
reaches the canopy as rapidly as possible, as reflected in the very long
successive GUs (more than 150 cm) observed in young trees (e.g. in ASD1)
(figure 1). Rapid longitudinal growth is enabled by the production of wood with
low inertia (low density) (figure 4) and high growth rate as previously
reported in tropical pioneers (Williamson et al., 2012). When the tree
reaches a sufficient height, and can intercept sufficient light, longitudinal
growth starts to slow down in favour of crown expansion (i.e. the
reiteration process, ASD2-3). At this time, the tree produces denser wood in
the peripheral part of the trunk in order to maintain its mechanical stature
(Fournier et al., 1991). Therefore, both the strong competition in
height growth in the juvenile stages (heliophilic temperament) and the
crown emergence/lateral expansion in the adult stages (long lived tree)
may be the main factors that explain the strong radial range of WD encountered
in this species.

A very wide range of wood density

The very low initial values of WD (0.2
g/cm3) also point to its heliophilic nature. This is one of the
species with the lowest WD values recorded in French Guiana, since only balsa
wood (Ochroma pyramidale) has a lower value (0.13 g/cm3)
(Rueda and Williamson, 1992). However, P. velutina also has a relatively
high WD, i.e. around 0.64 g/cm3, a value frequently
encountered in middle successional forest species. In P. velutina, we
thus found very high WD variability rarely reported in the literature except in
Schizolobium parahyba (Williamson et al., 2012). On the other
hand, such variations as we found in this species are not reported in the world
wood density database (Zanne et al., 2009) which gives a WD value of
about 0.40 g/cm3 for P. velutina, whereas we found a very wide
range of WD variability. This difference between studies is due to the fact
that measurements are usually limited to the trunk, and, as a result the real
variability of this pattern is probably not observed. In the present study on P.
velutina, WD variability in the trunk (in the axes below the main fork
supporting the crown) mainly ranged between 0.19 and 0.45 g/cm3,
whereas WD values inside the crown ranged from 0.45 to 0.64 g/cm3.
In studies that only consider certain parts of the tree, wide variability is
usually not reported. In our opinion, WD amplitude may often be
under-evaluated, since the crown has never previously been included in studies
of the WD in this species.

A significant difference between
height at the base and top of the trunk

In P. velutina, WD values in the
crowns were significantly higher than values found in the trunks. Two possible
explanations are that the canopy axes are (i) more exposed to wind, and (ii)
more ramified than the trunk, as the foliage of each branch subject to strong
windage. Stimulation of the branches by the wind may lead to the biosynthesis
of stiffer and less fragile wood. In fact, like in Schizolobium parahyba
(Williamson et al., 2012), in P. velutina, monopodial growth
partially reduces the risk of stem collapse and bending or breakage. The
difference in WD in the trunk and the crown observed in the big trees is more
rarely observed in small trees. In fact, in our sample, the crowns of the three
small trees were not dominant and not been exposed to wind, so an increase in
the WD of the crown would not have been necessary. Conversely, tree N°16 had
grown in the open (emergent tree), and had to stiffen its structures by
increasing its WD to stand up to the wind. This development resulted in a
radial gradient mainly observed in the trunk of the trees and less in the
crown. Contrary to the majority of previous studies in tropical pioneer species
(De Castro, 1993; Williamson and Wiemann, 2010), this gradient was clearly
non-linear in the trunk. Extreme radial increases in tropical trees were first
reported in Ochroma pyramidale (Whitmore, 1973). Since then, the number
of internationally published studies on radial variation in tropical trees has
drastically increased and the total number of species studied is now about 100
(Wiemann and Williamson, 1988, 1989; Rueda and Williamson, 1992; Butterfield et
al., 1993; De Castro et al., 1993; Woodcock et al., 2000;
Nock et al., 2009; Williamson and Wiemann, 2010, 2011), except
Williamson et al. (2012) and Osazuwa-Peters et
al. (2014) and the present study, few showed a curvilinear radial increase.
In fact, tree growth is rarely symmetric around the
trunk (Williamson and Wiemann, 2011). We observed differences in the pattern of
radial variation between two radii within one tree. These differences are due
to how the tree responds to local environmental conditions, the reorientation
of the stems for better access to light often leads to eccentric growth and the
production of tension wood (Pruyn et al., 2000).

Variation of WD is essentially
explained at the within tree level

Whereas some results show that the bulk
of WD variations is first explained at the inter-specific level followed by
within-radius level and among-conspecific level (Osazuwa et al., 2014),
our variance component analysis underlines a different pattern. We assume that
this difference is afforded by the integration of samples from different
height. As this study focused on a single species, our results are not directly
comparable with studies involving several species but can be compared in a
relative way. Osazuwa et al. (2014) found higher percentage of WD
variance explained by the within-radius level than among conspecific level.
Here, the longitudinal factor is such important in explaining WD variation that
the within radius variation becomes secondary. We can first hypothesise that WD
variation in P. velutina follows a particular pattern not generalizable
to other species. However, Lehnebach (2015) showed the same trend in
16 Fabaceae species sampled at different heights, including P. velutina
and other representatives of the same genus. More interestingly, as both
longitudinal and radial variations explained almost all the variation of WD (~
99%), the variance explained between individuals, although already weak in
other studies (i.e. 4% in Osazuwa et al. 2014), is negligible
when accounting for variation with height. This observation provides
interesting perspectives regarding the estimation of the whole range of WD
covered by a species. Indeed, WD variations being essentially covered by the
intra-tree level, the whole range of WD would be better estimated by
replicating measurement at different positions within few individuals than
estimating few WD values on a lot of individuals.

Conclusion

Variations in basic wood density (WD)
were high at different scales: between sites, between ages, between trees and
within individual trees. Our very selective sampling, based on the ontogenic
development of the species, enabled us to access the expression of all this
variability. Contrary to a local measure of WD, the complete pattern of WD
provides satisfactory information on the temperament of the species. It also
makes it possible to propose a model of the local density necessary for a better
prediction of biomass / carbon models.

Acknowledgement

This work was carried out within the
framework of the DEGRAD project, with financial support from the European
Regional Development Fund (FEDER). We are grateful to Onoefé Ngwete and Soepe
Koese for helping us in the fieldwork and woodwork.